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International Conference on Inductive Logic Programming

ILP 2006: Inductive Logic Programming pp 379–393Cite as

ILP Through Propositionalization and Stochastic k-Term DNF Learning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4455))

Abstract

One promising family of search strategies to alleviate runtime and storage requirements of ILP systems is that of stochastic local search methods, which have been successfully applied to hard propositional tasks such as satisfiability. Stochastic local search algorithms for propositional satisfiability benefit from the ability to quickly test whether a truth assignment satisfies a formula. Because of that many possible solutions can be tested and scored in a short time. In contrast, testing whether a clause covers an example in ILP takes much longer, so that far fewer possible solutions can be tested in the same time. Therefore in this paper we investigate stochastic local search in ILP using a relational propositionalized problem instead of directly use the first-order clauses space of solutions.

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Author information

Authors and Affiliations

  1. Dept. of Systems Engineering and Computer Science - COPPE, Federal University of Rio de Janeiro (UFRJ),  

    Aline Paes & Gerson Zaverucha

  2. Dept. of Cybernetics - School of Electrical Engineering, Czech Institute of Technology in Prague,  

    Filip Železný

  3. Dept. of Biostatistics and Medical Informatics and, Dept. of Computer Sciences, University of Wisconsin,  

    David Page

  4. IBM India Research Laboratory and, Dept of CSE and Centre for Health Informatics, University of New South Wales, Sydney, Australia

    Ashwin Srinivasan

Authors
  1. Aline Paes
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  2. Filip Železný
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  3. Gerson Zaverucha
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  4. David Page
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  5. Ashwin Srinivasan
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Editor information

Stephen Muggleton Ramon Otero Alireza Tamaddoni-Nezhad

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Paes, A., Železný, F., Zaverucha, G., Page, D., Srinivasan, A. (2007). ILP Through Propositionalization and Stochastic k-Term DNF Learning. In: Muggleton, S., Otero, R., Tamaddoni-Nezhad, A. (eds) Inductive Logic Programming. ILP 2006. Lecture Notes in Computer Science(), vol 4455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73847-3_35

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  • DOI: https://doi.org/10.1007/978-3-540-73847-3_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73846-6

  • Online ISBN: 978-3-540-73847-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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